Many thanks for the prompt response.
However, I am afraid that it is not completely clear for me. I
apologize, I am not a statistician.
Sorry, may be what I will say make totally non sense, but what I
understood is the following:
Let's suppose that I need to predict cancer-specific survival using
the variables X and Y. What I need to do is to develop a model that
include these variables and predict cancer-specific survival using the
competing-risks regression. Then, I shall calculate the "predictions"
of this model at a certain time point, then I shall use these
prediction as an "endpoint", and predict it using a linear regression
model that include the same variables, i.e X and Y. Finally, I use the
coefficients of this final model to develop a nomogram. Is that
Many thanks again
Should I calculate the "prediction" of the competing-risks regression
model, and then use this "prediction" as an "endpoint" and predict it
using a linear regression by including the same variables as
On Fri, Jun 24, 2011 at 1:27 PM, Frank Harrell [via R]
Replace the Design package with the rms package. Â Use the ordinary linear
regression trick to predict the linear predictor from the competing risk
regression, then use nomogram on this new model (that merely represents the
fit of interest).
Firas Abdollah wrote:
Hi R users,
I'd like to draw a nomogram using a competing-risks regression (crr function
in R), rather than a cox regression. However, the nomogram function provided
in the Design package is not good for this purpose.
Do you have any suggestion.
I really appreciate your help
Department of Biostatistics, Vanderbilt University
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Firas Abdollah, MD
Dept. of Urology
San Raffaele Hospital
Via Olgettina 60, 20132, Milan, Italy
Tel. +39 02 2643 7286
Fax. +39 02 2643 7298
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